AIMC Topic: Pharmacovigilance

Clear Filters Showing 91 to 100 of 109 articles

Semiautomated Approach for Muscle Weakness Detection in Clinical Texts.

Studies in health technology and informatics Jun 26, 2020
The automated detection of adverse events in medical records might be a cost-effective solution for patient safety management or pharmacovigilance. Our group proposed an information extraction algorithm (IEA) for detecting adverse events in neurosurg...
Pharmacovigilance Information Storage and Retrieval Muscle Weakness Humans Electronic Health Records Natural Language Processing
View on PubMed DOI

Adverse drug event rates in pediatric pulmonary hypertension: a comparison of real-world data sources.

Journal of the American Medical Informatics Association : JAMIA Feb 1, 2020
OBJECTIVE: Real-world data (RWD) are increasingly used for pharmacoepidemiology and regulatory innovation. Our objective was to compare adverse drug event (ADE) rates determined from two RWD sources, electronic health records and administrative claim...
Male Child, Preschool Pharmacovigilance Child Hypertension, Pulmonary Regression Analysis Current Procedural Terminology Natural Language Processing Insurance, Health Retrospective Studies Electronic Health Records Drug-Related Side Effects and Adverse Reactions Female Humans
View on PubMed DOI

Application of Augmented Intelligence for Pharmacovigilance Case Seriousness Determination.

Drug safety Jan 1, 2020
INTRODUCTION: Identification of adverse events and determination of their seriousness ensures timely detection of potential patient safety concerns. Adverse event seriousness is a key factor in defining reporting timelines and is often performed manu...
Neural Networks, Computer Drug-Related Side Effects and Adverse Reactions Pharmacovigilance Humans Adverse Drug Reaction Reporting Systems
View on PubMed DOI

Deep neural networks ensemble for detecting medication mentions in tweets.

Journal of the American Medical Informatics Association : JAMIA Dec 1, 2019
OBJECTIVE: Twitter posts are now recognized as an important source of patient-generated data, providing unique insights into population health. A fundamental step toward incorporating Twitter data in pharmacoepidemiologic research is to automatically...
Deep Learning Social Media Natural Language Processing Humans Neural Networks, Computer Pharmaceutical Preparations Pharmacovigilance
View on PubMed DOI

Learning to detect and understand drug discontinuation events from clinical narratives.

Journal of the American Medical Informatics Association : JAMIA Oct 1, 2019
OBJECTIVE: Identifying drug discontinuation (DDC) events and understanding their reasons are important for medication management and drug safety surveillance. Structured data resources are often incomplete and lack reason information. In this article...
Natural Language Processing Area Under Curve Pharmacovigilance Product Surveillance, Postmarketing Drug Therapy Electronic Health Records Support Vector Machine Narration Humans Machine Learning
View on PubMed DOI

Prediction of Personal Experience Tweets of Medication Use via Contextual Word Representations.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Continuous monitoring the safe use of medication is an important task in pharmacovigilance. The first-hand experiences of medication effects come from the consumers of the pharmaceuticals. Social media have been considered as a possible alternative d...
Neural Networks, Computer Social Media Natural Language Processing Pharmacovigilance Electric Power Supplies
View on PubMed DOI

Comment on: "Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts".

Journal of the American Medical Informatics Association : JAMIA Jun 1, 2019
Natural Language Processing Drug-Related Side Effects and Adverse Reactions Data Mining Neural Networks, Computer Pharmacovigilance Humans Deep Learning Datasets as Topic Social Media
View on PubMed DOI

Reply to comment on: "Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts".

Journal of the American Medical Informatics Association : JAMIA Jun 1, 2019
We appreciate the detailed review provided by Magge et al1 of our article, "Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts." 2 In their letter, they present a subjectiv...
Pharmacovigilance Humans Deep Learning Neural Networks, Computer Social Media Drug-Related Side Effects and Adverse Reactions
View on PubMed DOI

Artificial Intelligence Within Pharmacovigilance: A Means to Identify Cognitive Services and the Framework for Their Validation.

Pharmaceutical medicine Apr 1, 2019
INTRODUCTION: Pharmacovigilance (PV) detects, assesses, and prevents adverse events (AEs) and other drug-related problems by collecting, evaluating, and acting upon AEs. The volume of individual case safety reports (ICSRs) increases yearly, but it is...
Databases, Factual Machine Learning Adverse Drug Reaction Reporting Systems Guideline Adherence Drug-Related Side Effects and Adverse Reactions Algorithms Humans Cognition Pharmacovigilance Patient Safety Artificial Intelligence Decision Making Workload
View on PubMed DOI

Artificial Intelligence and the Future of the Drug Safety Professional.

Drug safety Apr 1, 2019
The healthcare industry, and specifically the pharmacovigilance industry, recognizes the need to support the increasing amount of data received from individual case safety reports (ICSRs). To cope with this increase, more healthcare and qualified pro...
Pharmacovigilance Decision Making Machine Learning Humans Risk Management Algorithms Artificial Intelligence Drug-Related Side Effects and Adverse Reactions Health Personnel
View on PubMed DOI
Popular Topics
Recent Journals